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JavaScript
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pizzahut_stores

Search Pizza Hut restaurants by city, state, postal code, name, franchise code, or store number. Returns address, phone, online ordering status, and timezone for each match.

Instructions

Search Pizza Hut restaurants by city, state, postal code, name, franchise code, or store number. Returns Pizza Hut restaurants matching a city/state/postal code/name/franchise code/store number filter. At least one filter is required -- an unfiltered call would enumerate every US restaurant in one response, which this endpoint intentionally does not expose. Each restaurant carries its store number (the value /pizzahut/menu and /pizzahut/store take), full address with coordinates, phone, whether it currently accepts online orders, and its timezone.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cityNoRestaurant city
nameNoRestaurant name, partial match
sortNoSort order
stateNoRestaurant state, two-letter code
is_archivedNoSet true to include archived/closed restaurant records, which the upstream default (unset) already excludes. Set false to make that exclusion explicit
max_resultsNoMaximum restaurants to return, 1-50 (default 20)
postal_codeNoRestaurant postal code
store_numberNoExact store number
franchise_codeNoExact franchise/operator code
accepting_online_ordersNoRestrict to restaurants currently accepting (true) or not accepting (false) online orders. Unfiltered (upstream default) unless set
appear_in_store_resultsNoRestrict to restaurants Pizza Hut's own storefront marks customer-facing. Unfiltered (upstream default) unless set -- passing true returns zero results for every region tested during research, so it is not defaulted on

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.17.5
    • addedInput schema / properties / sort / enum
      Added value: +[
+  "store_number_asc",
+  "store_number_desc",
+  "name_asc",
+  "name_desc",
+  "franchise_code_asc",
+  "franchise_code_desc"
+]
  2. Addedv1.16.2

TDQS

A4.5/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full disclosure burden. It reveals a key behavioral constraint (no unfiltered enumeration), describes the output shape (store number, full address with coordinates, phone, online-order status, timezone), and indicates a US-only scope. It doesn't mention pagination or filter combination semantics, but the core behavior is adequately transparent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is reasonably concise and front-loaded with the search verb and filter list Typical of a good definition. However, the first two sentences repeat the same filter enumeration ('by city...' and 'matching a city/state/postal code/name/franchise code/store number filter'), which is slightly redundant and could be tightened.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the 11 optional parameters and no output schema, the description covers the essential context: search filters, the requirement for at least one filter, and the rich output fields including linkage to other tools. It does not explicitly state how multiple filters combine (AND vs OR), but the schema's per-filter descriptions and the description's overall clarity mitigate this gap.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3. The description adds meaningful context beyond the schema by mandating at least one filter (contrasting with schema's empty required array) and explaining that the store_number output is consumed by other Pizza Hut endpoints. This is useful, actionable semantic guidance.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb ('Search') and resource ('Pizza Hut restaurants'), and enumerates the filter dimensions (city, state, postal code, name, franchise code, store number). It differentiates itself from sibling tools like pizzahut_menu and pizzahut_store by clarifying that it returns store numbers used as inputs to those endpoints.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly states that at least one filter is required and explains why (an unfiltered call would enumerate every US restaurant, which the endpoint intentionally does not expose). It also tells an agent how to use the results by noting the store number is what /pizzahut/menu and /pizzahut/store take, effectively pointing to the correct follow-up tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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